Rime launches Prism composable speech-to-speech model for enterprise voice agents

Voice AI company Rime launched Prism on 28 October 2026, an end-to-end speech-to-speech model built for regulated customer-service and enterprise phone agents. Traditional speech-to-speech models map audio directly to audio as a black box, preventing compliance teams from intercepting forbidden phrases or enforcing exact pronunciation of account numbers and drug names. Prism solves this by emitting an inspectable text checkpoint a few milliseconds before synthesising audio, allowing policy guardrails, phonemic conditioning, and parallel tool calls to execute mid-turn without cascading STT-to-LLM-to-TTS latency.

On the Artificial Analysis τ-Voice benchmark, Prism ranks first overall at 56.6 and reaches 82.5 on telecom customer-support workflows, compared with 45.6 for OpenAI’s GPT-Live-1. Model response latency averages roughly 300ms, yielding a 0.57-second time-to-first-audio that is about half the wait of GPT-Live-1, GPT-Realtime-2.1, and Gemini 3.8 Live.

Enterprise teams can fine-tune Prism with supervised fine-tuning (SFT) and reinforcement learning (RL) on their own historical call logs, and deploy via Rime’s WebSocket API, SDKs, or self-hosted private cloud containers.